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Applying the structural equation model rule-based fuzzy system with genetic algorithm for trading in currency market

Author

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  • Su, EnDer
  • Fen, Yu-Gin

Abstract

The present study uses the structural equation model (SEM) to analyze the correlations between various economic indices pertaining to latent variables, such as the New Taiwan Dollar (NTD) value, the United States Dollar (USD) value, and USD index. In addition, a risk factor of volatility of currency returns is considered to develop a risk-controllable fuzzy inference system. The rational and linguistic knowledge-based fuzzy rules are established based on the SEM model and then optimized using the genetic algorithm. The empirical results reveal that the fuzzy logic trading system using the SEM indeed outperforms the buy-and-hold strategy. Moreover, when considering the risk factor of currency volatility, the performance appears significantly better. Remarkably, the trading strategy is apparently affected when the USD value or the volatility of currency returns shifts into either a higher or lower state.

Suggested Citation

  • Su, EnDer & Fen, Yu-Gin, 2011. "Applying the structural equation model rule-based fuzzy system with genetic algorithm for trading in currency market," MPRA Paper 35474, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:35474
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    References listed on IDEAS

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    More about this item

    Keywords

    Knowledge-based Systems; Fuzzy Sets; Structural Equation Model (SEM); Genetic Algorithm (GA); Currency Volatility;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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